Research

Anthropogenic destruction of biosphere integrity is rapidly progressing. It even affects remote high mountain regions, questioning their role as biodiversity refuges in times of climate change. Although cold-determined alpine ecosystems are globally distributed, they are often very small-scale and fragmented, so that their disproportionally rich and unique vascular plant diversity is highly threatened through impacts of rising temperatures. This project will use the international GLORIA (https://gloria.ac.at) data set to understand changes in alpine plant diversity in summit zones that have been observed globally since the beginning of this century. By a worldwide compilation of standardised alpine vegetation data and integration of data on ecological drivers, the planned analyses deal with three main hypotheses: (1) changes in species numbers and composition are related to regional velocities of climate change, (2) combinations of reduced cold stress and increased drought stress accelerates loss of alpine plant diversity and (3) small-ranged species are overrepresented among declining and widespread ones among the gaining plants, being particularly worrisome in isolated small-scale alpine regions. We will use (1) data from repeated recordings of permanent plots, distributed over 100 alpine regions of the main mountain systems on Earth, combined with (2) remote sensing data of topography, changes in vegetation greenness and snow cover, (3) in situ-measured soil temperature and gridded climate data series as well as (4) data of species’ overall distribution and their thermic and hydrological niches in order to analyse and assess the magnitude and rates of biodiversity changes in relation to the main drivers.

In recent years, the use of terrestrial laser scanners (TLS) and airborne laser scanning (ALS) to characterize forests has made considerable progress and can be used both to record individual trees and thus biomass and carbon stocks and to monitor changes (growth, turnover). In evergreen tropical forests, such evaluations face the challenge that it is not possible to measure in a leafless state, which limits the view of trunks and branches and thus makes it difficult to calculate trunk sizes. In 2024, LIDAR surveys were carried out in La Gamba, Costa Rica, in primary, secondary forests and reforestation areas with planted trees using modern TLS and ALS systems. These data are to be analyzed as part of the project. First, individual TLS scans must be linked and the trees segmented, then these results will be checked with direct measurements of the trees on site and, as far as possible, the allometric model used for biomass calculation will be improved.

Impacts of climate change on alpine vegetation are already emerging, especially the accelerating accumulation of colonisers from lower elevations on mountain summits. The underlying upward movement of the alpine flora seems to be in line with modelling studies that predict major habitat loss and widespread local to regional extinction of high-elevation species under climate warming. However, in the few cases where sufficient data allowed for quantifying the magnitude of upward shifts observed so far these shifts appeared much weaker than the warming assumed to drive them. One possible explanation is a pronounced inertia in distribution patterns resulting in the accumulation of a so-called extinction debt. An alternative explanation is the pronounced ruggedness and associated variation of micro-climates of the high-mountain terrain which might efficiently buffer species against climate warming. Other than spatial distributions, vital rates of plants will likely respond rapidly to a changing climate. Modelling the spatial distribution and temporal change of population growth rates (Demographic dispersal modelling DDM) is hence an alternative to conventional distribution modelling (SDM) which is less affected by potential disequilibria of species and environmental conditions. In the proposed project we aim to expand the dataset collected within the previous project MICROCLIM in order to fit and project both SDMs and DDMs across the alpine and nival landscape of the central part of the Tyrolean Alps. Model projections will be evaluated against GLORIA long-term monitoring data. Based on these model projections we aim to tackle the following questions: (1) How much of their currently suitable area will alpine plants lose under climate change until the end of the century according to SDMs fitted and projected on a 1m resolution? (2) Are these predicted losses significantly lower than those forecasted by models fit and projected at coarser spatial resolutions? (3) Do DDMs predict more pronounced losses than SDMs because they are better capable of de-tecting a likely current disequilibrium between climate and species distribution? (4) Do differences between SDM and DDM projections depend on species traits? (5) Where, within the study area, do both SDMs and DDMs predict major refugia of the high-mountain flora in warmer world?